RETRACTED ARTICLE: Intelligent traffic monitoring and traffic diagnosis analysis based on neural network algorithm

• Published in: Neural computing & applications Vol. 33; no. 14; pp. 8107 - 8117
• Main Authors: Wang, Yantao, Wang, Quan, Suo, Daxiang, Wang, Tiezheng
• Format: Journal Article
• Language: English
• Published: London Springer London 01.07.2021; Springer Nature B.V
• Subjects: Artificial Intelligence; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Data Mining and Knowledge Discovery; Image Processing and Computer Vision; Probability and Statistics in Computer Science; S. I : Intelligent Computing Methodologies in Machine learning for IoT Applications; Special Issue on Intelligent Computing Methodologies in Machine learning for IoT Applications; Intelligent transportation; Neural network algorithm; Intelligent detection; Abnormal recognition; Intelligent diagnosis
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-020-04899-3

Traffic sign recognition and lane detection play an important role in traffic flow planning, avoiding traffic accidents, and alleviating traffic chaos. At present, the traffic intelligent recognition rate still needs to be improved. In view of this, based on the neural network algorithm, this study constructs an intelligent transportation system based on neural network algorithm, and combines machine vision technology to carry out intelligent monitoring and intelligent diagnosis of traffic system. In addition, this study discusses in detail the core of the monitoring system: multi-target tracking algorithm, and introduces the complete implementation process and details of the system, and highlights the implementation and tracking effect of the multi-target tracker. Finally, this study uses case identification to analyze the effectiveness of the algorithm proposed by this paper. The research results show that the proposed method has certain practical effects and can be used as a reference for subsequent system construction.